Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "161" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 34 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 34 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2460017 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.187292 | 27.648953 | 0.325294 | -0.077400 | 0.857391 | 0.836668 | 0.038313 | 1.148220 | 0.5854 | 0.4702 | 0.3177 | nan | nan |
| 2460016 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.190736 | 31.321820 | 0.397464 | -0.123680 | 0.758036 | 0.048159 | -0.397051 | 0.911927 | 0.5918 | 0.4796 | 0.3191 | nan | nan |
| 2460015 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.171039 | 32.381761 | 0.428086 | 0.013297 | 0.959108 | 0.555172 | -0.322561 | 2.539011 | 0.6019 | 0.4819 | 0.3179 | nan | nan |
| 2460014 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.720247 | 30.131949 | 0.232218 | -0.284694 | 0.036919 | 1.731496 | 0.135582 | 1.779202 | 0.5777 | 0.4539 | 0.3246 | nan | nan |
| 2460013 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.119248 | 32.681337 | 0.424878 | -0.109792 | 1.019765 | 0.484143 | -0.157268 | 1.149490 | 0.5955 | 0.4824 | 0.3227 | nan | nan |
| 2460012 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.035980 | 30.913428 | 0.251700 | -0.277414 | 1.244901 | 0.635701 | 0.492082 | 1.820618 | 0.5852 | 0.4753 | 0.3187 | nan | nan |
| 2460011 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.045104 | 32.278314 | 0.108334 | -0.511003 | 1.350221 | 1.620070 | 0.068283 | 0.598891 | 0.6070 | 0.5028 | 0.3153 | nan | nan |
| 2460010 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.343970 | 35.592460 | 0.051416 | -0.125271 | 0.707570 | 0.870812 | -0.183762 | 0.944278 | 0.6183 | 0.5142 | 0.3155 | nan | nan |
| 2460009 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.099260 | 33.426618 | 0.297068 | -0.019113 | 0.610687 | 0.932718 | -0.588188 | 0.485049 | 0.6195 | 0.5178 | 0.3190 | nan | nan |
| 2460008 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.494606 | 38.642167 | 0.226225 | -0.157597 | -0.086493 | 0.981128 | 0.561972 | 0.548686 | 0.6623 | 0.5783 | 0.2797 | nan | nan |
| 2460007 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.181081 | 29.653625 | 0.331654 | 0.036767 | 0.575957 | 0.479387 | -0.069224 | 1.003892 | 0.6286 | 0.5274 | 0.3050 | nan | nan |
| 2459999 | digital_ok | 0.00% | 98.91% | 99.25% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.2598 | 0.2254 | 0.1851 | nan | nan |
| 2459998 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.387318 | 26.268092 | 0.258098 | -0.122347 | 0.579095 | 0.894666 | -0.263376 | 0.602161 | 0.6166 | 0.5082 | 0.3412 | nan | nan |
| 2459997 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.534559 | 28.899944 | 0.225804 | -0.033927 | 0.423698 | 0.962703 | -0.142858 | 0.758705 | 0.6263 | 0.5167 | 0.3439 | nan | nan |
| 2459996 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.285990 | 31.015432 | 0.641828 | 0.110154 | 0.476167 | 0.972446 | -0.200247 | 0.126885 | 0.6391 | 0.5261 | 0.3541 | nan | nan |
| 2459995 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.590011 | 31.477722 | 0.150733 | -0.267175 | 0.528496 | 0.651987 | -0.290988 | 0.104375 | 0.6221 | 0.5124 | 0.3452 | nan | nan |
| 2459994 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.687936 | 30.549682 | 0.208448 | -0.123848 | 0.802851 | 1.340269 | 2.244956 | 3.561609 | 0.6154 | 0.5005 | 0.3442 | nan | nan |
| 2459993 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -1.048097 | 30.814739 | -0.036330 | -0.369227 | 0.243458 | 1.693242 | -0.500090 | 0.749369 | 0.5976 | 0.5046 | 0.3425 | nan | nan |
| 2459991 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -1.096651 | 34.791317 | 0.120592 | -0.262542 | 0.248695 | 1.277266 | -0.345985 | 0.450808 | 0.6331 | 0.5064 | 0.3509 | nan | nan |
| 2459990 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.729528 | 28.668063 | 0.157982 | -0.314807 | 0.476953 | 1.536282 | -0.476341 | 0.936739 | 0.6302 | 0.5041 | 0.3460 | nan | nan |
| 2459989 | digital_ok | 100.00% | 96.81% | 97.46% | 0.00% | - | - | 200.559429 | 201.027058 | inf | inf | 2884.303574 | 2846.344299 | 4522.274551 | 4370.875285 | 0.5348 | 0.4722 | 0.2600 | nan | nan |
| 2459988 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -1.004167 | 34.065336 | 0.095270 | -0.466396 | 0.214737 | 2.026794 | -0.466583 | 1.017283 | 0.6255 | 0.5110 | 0.3393 | nan | nan |
| 2459987 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.658559 | 28.919864 | 0.081660 | -0.281705 | 0.257580 | 0.812559 | 0.111346 | 1.358406 | 0.6346 | 0.5191 | 0.3381 | nan | nan |
| 2459986 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.732925 | 34.676290 | 0.113200 | -0.418362 | 0.239047 | 1.446510 | -0.270256 | 1.084192 | 0.6524 | 0.5556 | 0.2987 | nan | nan |
| 2459985 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.742360 | 32.255039 | 0.104427 | -0.342822 | -0.089037 | 0.720099 | -0.391900 | 1.577891 | 0.6339 | 0.5173 | 0.3455 | nan | nan |
| 2459984 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.725061 | 31.874529 | -0.425881 | -0.289909 | 0.370080 | 2.200087 | 1.342922 | 2.625696 | 0.6493 | 0.5399 | 0.3237 | nan | nan |
| 2459983 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -1.091898 | 30.412828 | 0.171010 | -0.392760 | -0.219363 | 1.583206 | -0.302400 | 1.061725 | 0.6627 | 0.5720 | 0.2851 | nan | nan |
| 2459982 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -1.115323 | 23.778531 | 0.337552 | -0.035319 | 0.566901 | 0.841085 | 0.115839 | -0.126966 | 0.7122 | 0.6110 | 0.2564 | nan | nan |
| 2459981 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.992467 | 27.440913 | 0.064900 | -0.540940 | -0.071780 | 1.715083 | -0.490780 | 0.247909 | 0.6335 | 0.5180 | 0.3423 | nan | nan |
| 2459980 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.822755 | 26.017563 | -0.034342 | -0.549964 | -0.167578 | 1.299413 | 0.099857 | 0.196091 | 0.6768 | 0.5805 | 0.2745 | nan | nan |
| 2459979 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -1.033837 | 28.237109 | -0.142308 | -0.526050 | -0.077863 | 1.001467 | -0.467111 | 0.184193 | 0.6261 | 0.5109 | 0.3430 | nan | nan |
| 2459978 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.953289 | 28.718017 | -0.110730 | -0.561960 | 0.158170 | 1.433372 | -0.617589 | 0.463935 | 0.6267 | 0.5113 | 0.3468 | nan | nan |
| 2459977 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.845908 | 29.683410 | -0.083015 | -0.406062 | 0.547903 | 1.659527 | 0.897616 | 2.268832 | 0.5938 | 0.4794 | 0.3157 | nan | nan |
| 2459976 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.958335 | 28.802548 | -0.035429 | -0.557145 | 0.023031 | 0.995014 | -0.600390 | 0.054336 | 0.6314 | 0.5187 | 0.3388 | nan | nan |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 27.648953 | 27.648953 | -0.187292 | -0.077400 | 0.325294 | 0.836668 | 0.857391 | 1.148220 | 0.038313 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 31.321820 | 31.321820 | -0.190736 | -0.123680 | 0.397464 | 0.048159 | 0.758036 | 0.911927 | -0.397051 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 32.381761 | 32.381761 | -0.171039 | 0.013297 | 0.428086 | 0.555172 | 0.959108 | 2.539011 | -0.322561 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 30.131949 | -0.720247 | 30.131949 | 0.232218 | -0.284694 | 0.036919 | 1.731496 | 0.135582 | 1.779202 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 32.681337 | -0.119248 | 32.681337 | 0.424878 | -0.109792 | 1.019765 | 0.484143 | -0.157268 | 1.149490 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 30.913428 | -0.035980 | 30.913428 | 0.251700 | -0.277414 | 1.244901 | 0.635701 | 0.492082 | 1.820618 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 32.278314 | -0.045104 | 32.278314 | 0.108334 | -0.511003 | 1.350221 | 1.620070 | 0.068283 | 0.598891 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 35.592460 | -0.343970 | 35.592460 | 0.051416 | -0.125271 | 0.707570 | 0.870812 | -0.183762 | 0.944278 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 33.426618 | -0.099260 | 33.426618 | 0.297068 | -0.019113 | 0.610687 | 0.932718 | -0.588188 | 0.485049 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 38.642167 | 38.642167 | -0.494606 | -0.157597 | 0.226225 | 0.981128 | -0.086493 | 0.548686 | 0.561972 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 29.653625 | -0.181081 | 29.653625 | 0.331654 | 0.036767 | 0.575957 | 0.479387 | -0.069224 | 1.003892 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 26.268092 | -0.387318 | 26.268092 | 0.258098 | -0.122347 | 0.579095 | 0.894666 | -0.263376 | 0.602161 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 28.899944 | -0.534559 | 28.899944 | 0.225804 | -0.033927 | 0.423698 | 0.962703 | -0.142858 | 0.758705 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 31.015432 | -0.285990 | 31.015432 | 0.641828 | 0.110154 | 0.476167 | 0.972446 | -0.200247 | 0.126885 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 31.477722 | -0.590011 | 31.477722 | 0.150733 | -0.267175 | 0.528496 | 0.651987 | -0.290988 | 0.104375 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 30.549682 | -0.687936 | 30.549682 | 0.208448 | -0.123848 | 0.802851 | 1.340269 | 2.244956 | 3.561609 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 30.814739 | -1.048097 | 30.814739 | -0.036330 | -0.369227 | 0.243458 | 1.693242 | -0.500090 | 0.749369 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 34.791317 | -1.096651 | 34.791317 | 0.120592 | -0.262542 | 0.248695 | 1.277266 | -0.345985 | 0.450808 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 28.668063 | 28.668063 | -0.729528 | -0.314807 | 0.157982 | 1.536282 | 0.476953 | 0.936739 | -0.476341 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Power | inf | 201.027058 | 200.559429 | inf | inf | 2846.344299 | 2884.303574 | 4370.875285 | 4522.274551 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 34.065336 | 34.065336 | -1.004167 | -0.466396 | 0.095270 | 2.026794 | 0.214737 | 1.017283 | -0.466583 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 28.919864 | -0.658559 | 28.919864 | 0.081660 | -0.281705 | 0.257580 | 0.812559 | 0.111346 | 1.358406 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 34.676290 | 34.676290 | -0.732925 | -0.418362 | 0.113200 | 1.446510 | 0.239047 | 1.084192 | -0.270256 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 32.255039 | 32.255039 | -0.742360 | -0.342822 | 0.104427 | 0.720099 | -0.089037 | 1.577891 | -0.391900 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 31.874529 | -0.725061 | 31.874529 | -0.425881 | -0.289909 | 0.370080 | 2.200087 | 1.342922 | 2.625696 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 30.412828 | -1.091898 | 30.412828 | 0.171010 | -0.392760 | -0.219363 | 1.583206 | -0.302400 | 1.061725 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 23.778531 | -1.115323 | 23.778531 | 0.337552 | -0.035319 | 0.566901 | 0.841085 | 0.115839 | -0.126966 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 27.440913 | 27.440913 | -0.992467 | -0.540940 | 0.064900 | 1.715083 | -0.071780 | 0.247909 | -0.490780 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 26.017563 | 26.017563 | -0.822755 | -0.549964 | -0.034342 | 1.299413 | -0.167578 | 0.196091 | 0.099857 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 28.237109 | -1.033837 | 28.237109 | -0.142308 | -0.526050 | -0.077863 | 1.001467 | -0.467111 | 0.184193 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 28.718017 | 28.718017 | -0.953289 | -0.561960 | -0.110730 | 1.433372 | 0.158170 | 0.463935 | -0.617589 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 29.683410 | -0.845908 | 29.683410 | -0.083015 | -0.406062 | 0.547903 | 1.659527 | 0.897616 | 2.268832 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 161 | N13 | digital_ok | nn Shape | 28.802548 | 28.802548 | -0.958335 | -0.557145 | -0.035429 | 0.995014 | 0.023031 | 0.054336 | -0.600390 |